Build the Path Forward
At Path Robotics, we’re attacking a trillion dollar opportunity - doing things that have never been done before to support an industry hurting from a lack of skilled labor. Big, hard problems are what Path tackles every day and our people are our greatest asset to get that job done. Our intelligent, hardworking team of people do the impossible every single day, yet remain incredibly kind, humble, and always ready to support one another.
We're on the lookout for an outstanding individual to play a crucial role in the intersection of welding science and artificial intelligence. As a Staff Machine Learning Engineer, you'll apply your expertise in computer vision, machine learning, generative AI, multi-modal models and Python programming. This combination will be pivotal in driving innovation to tackle intricate challenges in our field. Collaborating closely with our exceptional AI, robotics, weld science, and software engineering teams you'll be at the forefront of developing groundbreaking AI-driven robotic welding methods.
What You’ll Do
Research and Development:
- Leading R&D initiatives aimed at addressing challenges related to novel problems in the welding domain, using image and point cloud data as input, and solving unique domain specific welding problems
- Design and implement novel techniques and methods for advancing Large Language Models (LLMs), multimodal models, and embodied agents.
- Contribute to the development of innovative algorithms and approaches to address challenges in natural language understanding, multimodal integration, and agent embodiment.
- Build foundational computer vision and machine learning models that can transform the manufacturing industry
- Design and execute experiments to evaluate the efficacy of machine learning systems, encompassing processes, parameters, algorithms, and equipment, with a focus on deep neural network models
Infrastructure and Data Pipelines:
- Engineer robust infrastructure and scalable data pipelines to support the scaling up of foundation models.
- Optimize existing processes and propose improvements to enhance efficiency and performance in handling large-scale datasets.
Technology Transfer:
- Collaborate closely with product groups to transfer research findings and technologies into practical applications.
- Work collaboratively to integrate research advancements into existing products or guide the development of new solutions based on the research outcomes.
Collaboration with External Researchers:
- Foster collaborations with external researchers, academia, and industry experts to stay abreast of the latest developments in NLP, multimodal models, and embodied agents.
- Contribute to joint research efforts, attend conferences, and actively participate in the scientific community.
Who you are
- PhD in Computer Science focusing on Machine Learning, or equivalent practical experience/education, with a strong foundation in neural networks and data-driven models.
- Over 5 years of research experience dedicated to pioneering novel machine learning algorithms, including more than 3 years of industry exposure to designing, developing, and deploying real-world deep neural network models using Python.
- Have a strong understanding and demonstration of test-driven coding standards with experience deploying production code.
- Enthusiastic about joining an early-stage venture-backed company, recognizing the immediate and direct influence your work will have.
- Demonstrated ownership, dedication, and enthusiasm for overcoming challenges.
- Nice to have: C++ and ROS experience
Best way to stand out
- Proven track record in publishing at conferences (e.g. NeurIPS, ICLR, CVPR, ICML)
- Open-source contributions related to multimodal AI or embodied intelligence
